Overview

Dataset statistics

Number of variables6
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory58.3 B

Variable types

Text1
Numeric4
Categorical1

Dataset

Description정보통신기사, 무선통신사 등 한국방송통신전파진흥원에서 발급하는 자격증에 대한 발급/재발급 통계 현황 입니다.
Author한국방송통신전파진흥원
URLhttps://www.data.go.kr/data/15042442/fileData.do

Alerts

신규발급 is highly overall correlated with 재발급 and 3 other fieldsHigh correlation
재발급 is highly overall correlated with 신규발급 and 3 other fieldsHigh correlation
정정건수 is highly overall correlated with 신규발급 and 3 other fieldsHigh correlation
합계 is highly overall correlated with 신규발급 and 3 other fieldsHigh correlation
정정발급 is highly overall correlated with 신규발급 and 3 other fieldsHigh correlation
정정발급 is highly imbalanced (50.2%)Imbalance
종목 has unique valuesUnique
신규발급 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:58:52.133859
Analysis finished2023-12-12 13:58:54.169759
Duration2.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종목
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T22:58:54.349441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length8.48
Min length6

Characters and Unicode

Total characters212
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row전파전자통신기사
2nd row전파전자통신산업기사
3rd row전파전자통신기능사
4th row무선설비기사
5th row무선설비산업기사
ValueCountFrequency (%)
전파전자통신기사 1
 
4.0%
제3급아마추어무선기사(전화급 1
 
4.0%
통신선로기능사 1
 
4.0%
통신선로산업기사 1
 
4.0%
통신설비기능장 1
 
4.0%
방송통신기능사 1
 
4.0%
방송통신산업기사 1
 
4.0%
방송통신기사 1
 
4.0%
정보통신산업기사 1
 
4.0%
정보통신기사 1
 
4.0%
Other values (15) 15
60.0%
2023-12-12T22:58:54.715253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 24
 
11.3%
기 23
 
10.8%
신 18
 
8.5%
통 17
 
8.0%
선 14
 
6.6%
무 12
 
5.7%
전 8
 
3.8%
급 7
 
3.3%
제 6
 
2.8%
능 6
 
2.8%
Other values (30) 77
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 203
95.8%
Decimal Number 5
 
2.4%
Close Punctuation 2
 
0.9%
Open Punctuation 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 24
 
11.8%
기 23
 
11.3%
신 18
 
8.9%
통 17
 
8.4%
선 14
 
6.9%
무 12
 
5.9%
전 8
 
3.9%
급 7
 
3.4%
제 6
 
3.0%
능 6
 
3.0%
Other values (24) 68
33.5%
Decimal Number
ValueCountFrequency (%)
3 2
40.0%
2 1
20.0%
1 1
20.0%
4 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 203
95.8%
Common 9
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 24
 
11.8%
기 23
 
11.3%
신 18
 
8.9%
통 17
 
8.4%
선 14
 
6.9%
무 12
 
5.9%
전 8
 
3.9%
급 7
 
3.4%
제 6
 
3.0%
능 6
 
3.0%
Other values (24) 68
33.5%
Common
ValueCountFrequency (%)
3 2
22.2%
) 2
22.2%
( 2
22.2%
2 1
11.1%
1 1
11.1%
4 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 203
95.8%
ASCII 9
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 24
 
11.8%
기 23
 
11.3%
신 18
 
8.9%
통 17
 
8.4%
선 14
 
6.9%
무 12
 
5.9%
전 8
 
3.9%
급 7
 
3.4%
제 6
 
3.0%
능 6
 
3.0%
Other values (24) 68
33.5%
ASCII
ValueCountFrequency (%)
3 2
22.2%
) 2
22.2%
( 2
22.2%
2 1
11.1%
1 1
11.1%
4 1
11.1%

신규발급
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean743.96
Minimum7
Maximum7327
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T22:58:54.873402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile11.8
Q156
median238
Q3938
95-th percentile2079.2
Maximum7327
Range7320
Interquartile range (IQR)882

Descriptive statistics

Standard deviation1484.2989
Coefficient of variation (CV)1.9951327
Kurtosis17.386459
Mean743.96
Median Absolute Deviation (MAD)223
Skewness3.9445008
Sum18599
Variance2203143.3
MonotonicityNot monotonic
2023-12-12T22:58:55.014493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
97 1
 
4.0%
7 1
 
4.0%
83 1
 
4.0%
1372 1
 
4.0%
71 1
 
4.0%
112 1
 
4.0%
29 1
 
4.0%
15 1
 
4.0%
50 1
 
4.0%
282 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
7 1
4.0%
11 1
4.0%
15 1
4.0%
23 1
4.0%
29 1
4.0%
50 1
4.0%
56 1
4.0%
71 1
4.0%
83 1
4.0%
97 1
4.0%
ValueCountFrequency (%)
7327 1
4.0%
2256 1
4.0%
1372 1
4.0%
1150 1
4.0%
1041 1
4.0%
985 1
4.0%
938 1
4.0%
934 1
4.0%
656 1
4.0%
488 1
4.0%

재발급
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean189.16
Minimum5
Maximum1293
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T22:58:55.159260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q119
median130
Q3210
95-th percentile575
Maximum1293
Range1288
Interquartile range (IQR)191

Descriptive statistics

Standard deviation277.48163
Coefficient of variation (CV)1.466915
Kurtosis10.40866
Mean189.16
Median Absolute Deviation (MAD)111
Skewness2.9504331
Sum4729
Variance76996.057
MonotonicityNot monotonic
2023-12-12T22:58:55.344497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
5 3
 
12.0%
30 1
 
4.0%
73 1
 
4.0%
131 1
 
4.0%
185 1
 
4.0%
157 1
 
4.0%
10 1
 
4.0%
19 1
 
4.0%
151 1
 
4.0%
125 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
5 3
12.0%
9 1
 
4.0%
10 1
 
4.0%
16 1
 
4.0%
19 1
 
4.0%
28 1
 
4.0%
30 1
 
4.0%
34 1
 
4.0%
73 1
 
4.0%
125 1
 
4.0%
ValueCountFrequency (%)
1293 1
4.0%
592 1
4.0%
507 1
4.0%
323 1
4.0%
307 1
4.0%
248 1
4.0%
210 1
4.0%
185 1
4.0%
157 1
4.0%
151 1
4.0%

정정발급
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
0
20 
1
3 
2
 
1
6
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)8.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 20
80.0%
1 3
 
12.0%
2 1
 
4.0%
6 1
 
4.0%

Length

2023-12-12T22:58:55.495761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:58:55.618721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 20
80.0%
1 3
 
12.0%
2 1
 
4.0%
6 1
 
4.0%

정정건수
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean189.6
Minimum5
Maximum1299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T22:58:55.753678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q119
median130
Q3210
95-th percentile575.8
Maximum1299
Range1294
Interquartile range (IQR)191

Descriptive statistics

Standard deviation278.58153
Coefficient of variation (CV)1.4693118
Kurtosis10.461253
Mean189.6
Median Absolute Deviation (MAD)111
Skewness2.9579474
Sum4740
Variance77607.667
MonotonicityNot monotonic
2023-12-12T22:58:55.907718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
5 3
 
12.0%
30 1
 
4.0%
73 1
 
4.0%
131 1
 
4.0%
185 1
 
4.0%
158 1
 
4.0%
10 1
 
4.0%
19 1
 
4.0%
151 1
 
4.0%
125 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
5 3
12.0%
9 1
 
4.0%
10 1
 
4.0%
16 1
 
4.0%
19 1
 
4.0%
28 1
 
4.0%
30 1
 
4.0%
34 1
 
4.0%
73 1
 
4.0%
125 1
 
4.0%
ValueCountFrequency (%)
1299 1
4.0%
593 1
4.0%
507 1
4.0%
325 1
4.0%
307 1
4.0%
249 1
4.0%
210 1
4.0%
185 1
4.0%
158 1
4.0%
151 1
4.0%

합계
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean933.56
Minimum20
Maximum8626
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T22:58:56.044357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile21.6
Q180
median433
Q31171
95-th percentile2521.8
Maximum8626
Range8606
Interquartile range (IQR)1091

Descriptive statistics

Standard deviation1740.2081
Coefficient of variation (CV)1.864056
Kurtosis17.124904
Mean933.56
Median Absolute Deviation (MAD)378
Skewness3.9049952
Sum23339
Variance3028324.3
MonotonicityNot monotonic
2023-12-12T22:58:56.169238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
20 2
 
8.0%
127 1
 
4.0%
795 1
 
4.0%
214 1
 
4.0%
1557 1
 
4.0%
229 1
 
4.0%
122 1
 
4.0%
48 1
 
4.0%
55 1
 
4.0%
433 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
20 2
8.0%
28 1
4.0%
48 1
4.0%
55 1
4.0%
72 1
4.0%
80 1
4.0%
122 1
4.0%
127 1
4.0%
148 1
4.0%
214 1
4.0%
ValueCountFrequency (%)
8626 1
4.0%
2763 1
4.0%
1557 1
4.0%
1531 1
4.0%
1286 1
4.0%
1183 1
4.0%
1171 1
4.0%
1110 1
4.0%
795 1
4.0%
690 1
4.0%

Interactions

2023-12-12T22:58:53.602739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:52.327911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:52.858749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:53.251431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:53.723420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:52.625741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:52.942003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:53.347483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:53.815910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:52.694506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:53.050503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:53.430981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:53.897500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:52.781064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:53.134383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:58:53.514904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:58:56.269299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종목신규발급재발급정정발급정정건수합계
종목1.0001.0001.0001.0001.0001.000
신규발급1.0001.0000.9380.8770.9381.000
재발급1.0000.9381.0000.8791.0000.938
정정발급1.0000.8770.8791.0000.8790.877
정정건수1.0000.9381.0000.8791.0000.938
합계1.0001.0000.9380.8770.9381.000
2023-12-12T22:58:56.374609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신규발급재발급정정건수합계정정발급
신규발급1.0000.7300.7300.9580.542
재발급0.7301.0001.0000.8610.714
정정건수0.7301.0001.0000.8610.714
합계0.9580.8610.8611.0000.542
정정발급0.5420.7140.7140.5421.000

Missing values

2023-12-12T22:58:54.010828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:58:54.122398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

종목신규발급재발급정정발급정정건수합계
0전파전자통신기사9730030127
1전파전자통신산업기사77307380
2전파전자통신기능사93859215931531
3무선설비기사93424812491183
4무선설비산업기사2582100210468
5무선설비기능사2383232325563
6육상무선통신사115013601361286
7제한무선통신사73271293612998626
8항공무선통신사225650705072763
9해상무선통신사104113001301171
종목신규발급재발급정정발급정정건수합계
15정보통신기술사2350528
16정보통신기사98512501251110
17정보통신산업기사2821510151433
18방송통신기사5050555
19방송통신산업기사1550520
20방송통신기능사291901948
21통신설비기능장11210010122
22통신선로산업기사711571158229
23통신선로기능사137218501851557
24통신기기기능사831310131214